砂/页岩沉积物中油气储层的模式识别方法

Q4 Computer Science

模式识别与人工智能 Pub Date : 1992-08-30 DOI:10.1109/ICPR.1992.201818

Zheng-He Yao, Li-De Wu

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引用次数: 1

摘要

本文提出了一种混合结构和统计模式识别方法，用于砂/页岩沉积物中油气储层的识别。根据测井资料和地震资料得到的砂体基准剖面，采用基于树的区域检测方法对砂层进行检测，并采用基于Marr算子的聚类算法在检测砂层中寻找油气储层。通过实例验证了该方法的有效性。

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A pattern recognition approach to detect oil/gas reservoirs in sand/shale sediments

A hybrid structural and statistical pattern recognition approach to detect oil/gas reservoirs in sand/shale sediments is presented in the paper. On the basis of the sand fiducial profile derived from log data and seismic data, a tree-based region-detecting method is used to detect sand layers, and a Marr's-operator-based clustering algorithm is used to find oil/gas reservoirs in the detected sand layers. The ability of the approach is demonstrated by a real-data example.<>

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来源期刊

模式识别与人工智能 Computer Science-Artificial Intelligence

CiteScore

1.60

自引率

0.00%

发文量

3316

期刊介绍：